Fine-scale movement decisions of tropical forest birds in a fragmented landscape.

The persistence of forest-dependent species in fragmented landscapes is fundamentally linked to the movement of individuals among subpopulations. The paths taken by dispersing individuals can be considered a series of steps built from individual route choices. Despite the importance of these fine-scale movement decisions, it has proved difficult to collect such data that reveal how forest birds move in novel landscapes. We collected unprecedented route information about the movement of translocated forest birds from two species in the highly fragmented tropical dry forest of Costa Rica. In this pasture-dominated landscape, forest remains in patches or riparian corridors, with lesser amounts of living fencerows and individual trees or "stepping stones." We used step selection functions to quantify how route choice was influenced by these habitat elements. We found that the amount of risk these birds were willing to take by crossing open habitat was context dependent. The forest-specialist Barred Antshrike (Thamnophilus doliatus) exhibited stronger selection for forested routes when moving in novel landscapes distant from its territory relative to locations closer to its territory. It also selected forested routes when its step originated in forest habitat. It preferred steps ending in stepping stones when the available routes had little forest cover, but avoided them when routes had greater forest cover. The forest-generalist Rufous-naped Wren (Campylorhynchus rufinucha) preferred steps that contained more pasture, but only when starting from non-forest habitats. Our results showed that forested corridors (i.e., riparian corridors) best facilitated the movement of a sensitive forest specialist through this fragmented landscape. They also suggested that stepping stones can be important in highly fragmented forests with little remaining forest cover. We expect that naturally dispersing birds and species with greater forest dependence would exhibit even stronger selection for forested routes than did the birds in our experiments.

Riparian corridors enhance movement of a forest specialist bird in fragmented tropical forest.

Riparian corridors and fencerows are hypothesized to increase the persistence of forest animals in fragmented landscapes by facilitating movement among suitable habitat patches. This function may be critically important for forest birds, which have declined dramatically in fragmented habitats. Unfortunately, direct evidence of corridor use has been difficult to collect at landscape scales and this limits support for corridors in conservation planning. Using telemetry and handheld GPS units, we examined the movement of forest birds by translocating territorial individuals of barred antshrikes (Thamnophilus doliatus; a forest specialist) and rufous-naped wrens (Campylorhynchus rufinucha; a forest generalist) 0.7-1.9 km from their territories in the highly fragmented tropical dry forest of Costa Rica. In each translocation, the directly intervening habitat comprised 1 of 3 treatments: forested riparian corridor, linear living fencerow, or open pasture. Antshrikes returned faster and with greater success in riparian corridors relative to pasture treatments. This species also traveled more directly in riparian corridor treatments, detoured to use forested routes in the other 2 treatments, and did not use fencerows even when they led directly to their home territories. By contrast, wrens were more likely to use fencerows when returning, and return time and success were equivalent among the 3 treatments. Both species crossed fewer gaps in tree cover during riparian corridor treatments than in fencerow or pasture treatments. We conclude that antshrikes, which may be representative of other forest specialists, use forested corridors for movement in this landscape and that fencerows are avoided as movement conduits.

Application of random effects to the study of resource selection by animals.

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.